Establishing a comprehensive host-parasite stable isotope database to unravel trophic relationships
Bibliographic record
Abstract
Over the past decades, stable isotopes have been infrequently used to characterise host-parasite trophic relationships. This is because we have not yet identified consistent patterns in stable isotope values between parasites and their host tissues across species, which are crucial for understanding host-parasite dynamics. To address this, we initiated a worldwide collaboration to establish a unique database of stable isotope values of novel host-parasite pairs, effectively doubling the existing data in published literature. This database includes nitrogen, carbon, and sulphur stable isotope values. We present 3213 stable isotope data entries, representing 586 previously unpublished host-parasite pairs. Additionally, while existing literature was particularly limited in sulphur isotope values, we tripled information on this crucial element. By publishing unreported host-parasite pairs from previously unsampled areas of the world and using appropriate host tissues, our dataset stands unparalleled. We anticipate that end-users will utilise our database to uncover generalisable patterns, deepening our understanding of the complexities of parasite-host relationships and driving future research efforts in stable isotope parasitology.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".